Triple
T36077063
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | JGK |
E1043524
|
entity |
| Predicate | relatedStationNameChinese |
—
|
GENERATED |
| Object | 济南西站 |
—
|
UNRECOGNIZED GENERATED |
How this triple was built (1 step)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedStationNameChinese Context triple: [JGK, relatedStationNameChinese, 济南西站]
-
A.
relatedStationNumber
Indicates that there is an associated or corresponding station identified by a particular station number.
-
B.
associatedStation
Indicates a relationship where one entity is linked or connected to a particular station as its relevant or related station.
-
C.
adjacentStationOnBeijingShanghaiHsr
Indicates that two stations are directly next to each other along the Beijing–Shanghai high-speed railway line, with no other station in between.
-
D.
nearbyStationName
chosen
Indicates that the predicate specifies the name of a station that is geographically close to a given reference point or entity.
-
E.
interchangeStation
Indicates a station where passengers can transfer between different routes, lines, or modes of transportation.
- F. None of above.
Provenance (1 batch)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f76e3154908190a6f702671c2bea08 |
completed | May 3, 2026, 3:48 p.m. |
Created at: May 3, 2026, 4:08 p.m.